{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas  as pd\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams[\"font.sans-serif\"] = [\"SimHei\"]\n",
    "plt.rcParams[\"axes.unicode_minus\"] = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "outputs": [
    {
     "data": {
      "text/plain": "    患者ID   姓名  年龄 性别  就诊次数  医疗费用   诊断    药物   治疗方案        入院日期\n0      1   张三  45  男     3   500   感冒   感冒药     休息  2023-07-01\n1      2   李四  32  女     2   700   发热   退烧药     休息  2023-07-02\n2      3   王五  60  男     1  1200  高血压   降压药   定期运动  2023-07-03\n3      4   赵六  28  女     4   800   感冒   感冒药     休息  2023-07-04\n4      5   刘七  50  男     2   600   胃炎   抗酸药   清淡饮食  2023-07-05\n5      6   陈八  65  女     1  1500  糖尿病   胰岛素   控制饮食  2023-07-06\n6      7   张九  38  男     3   900   头痛   止痛药     休息  2023-07-07\n7      8   李十  22  女     2   400   流感  抗病毒药     休息  2023-07-08\n8      9  王十一  55  男     1  1000  高血压   降压药   定期运动  2023-07-09\n9     10  赵十二  30  女     4   750   过敏  抗过敏药  避免过敏源  2023-07-10\n10    11  刘十三  40  男     2   550   胃炎   抗酸药   清淡饮食  2023-07-11\n11    12  陈十四  70  女     1  1800  糖尿病   胰岛素   控制饮食  2023-07-12\n12    13  张十五  25  男     3   950   感冒   感冒药     休息  2023-07-13\n13    14  李十六  28  女     2   650   发热   退烧药     休息  2023-07-14\n14    15  王十七  58  男     1  1300  高血压   降压药   定期运动  2023-07-15",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>患者ID</th>\n      <th>姓名</th>\n      <th>年龄</th>\n      <th>性别</th>\n      <th>就诊次数</th>\n      <th>医疗费用</th>\n      <th>诊断</th>\n      <th>药物</th>\n      <th>治疗方案</th>\n      <th>入院日期</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1</td>\n      <td>张三</td>\n      <td>45</td>\n      <td>男</td>\n      <td>3</td>\n      <td>500</td>\n      <td>感冒</td>\n      <td>感冒药</td>\n      <td>休息</td>\n      <td>2023-07-01</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2</td>\n      <td>李四</td>\n      <td>32</td>\n      <td>女</td>\n      <td>2</td>\n      <td>700</td>\n      <td>发热</td>\n      <td>退烧药</td>\n      <td>休息</td>\n      <td>2023-07-02</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>3</td>\n      <td>王五</td>\n      <td>60</td>\n      <td>男</td>\n      <td>1</td>\n      <td>1200</td>\n      <td>高血压</td>\n      <td>降压药</td>\n      <td>定期运动</td>\n      <td>2023-07-03</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>4</td>\n      <td>赵六</td>\n      <td>28</td>\n      <td>女</td>\n      <td>4</td>\n      <td>800</td>\n      <td>感冒</td>\n      <td>感冒药</td>\n      <td>休息</td>\n      <td>2023-07-04</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>5</td>\n      <td>刘七</td>\n      <td>50</td>\n      <td>男</td>\n      <td>2</td>\n      <td>600</td>\n      <td>胃炎</td>\n      <td>抗酸药</td>\n      <td>清淡饮食</td>\n      <td>2023-07-05</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>6</td>\n      <td>陈八</td>\n      <td>65</td>\n      <td>女</td>\n      <td>1</td>\n      <td>1500</td>\n      <td>糖尿病</td>\n      <td>胰岛素</td>\n      <td>控制饮食</td>\n      <td>2023-07-06</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>7</td>\n      <td>张九</td>\n      <td>38</td>\n      <td>男</td>\n      <td>3</td>\n      <td>900</td>\n      <td>头痛</td>\n      <td>止痛药</td>\n      <td>休息</td>\n      <td>2023-07-07</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>8</td>\n      <td>李十</td>\n      <td>22</td>\n      <td>女</td>\n      <td>2</td>\n      <td>400</td>\n      <td>流感</td>\n      <td>抗病毒药</td>\n      <td>休息</td>\n      <td>2023-07-08</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>9</td>\n      <td>王十一</td>\n      <td>55</td>\n      <td>男</td>\n      <td>1</td>\n      <td>1000</td>\n      <td>高血压</td>\n      <td>降压药</td>\n      <td>定期运动</td>\n      <td>2023-07-09</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>10</td>\n      <td>赵十二</td>\n      <td>30</td>\n      <td>女</td>\n      <td>4</td>\n      <td>750</td>\n      <td>过敏</td>\n      <td>抗过敏药</td>\n      <td>避免过敏源</td>\n      <td>2023-07-10</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>11</td>\n      <td>刘十三</td>\n      <td>40</td>\n      <td>男</td>\n      <td>2</td>\n      <td>550</td>\n      <td>胃炎</td>\n      <td>抗酸药</td>\n      <td>清淡饮食</td>\n      <td>2023-07-11</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>12</td>\n      <td>陈十四</td>\n      <td>70</td>\n      <td>女</td>\n      <td>1</td>\n      <td>1800</td>\n      <td>糖尿病</td>\n      <td>胰岛素</td>\n      <td>控制饮食</td>\n      <td>2023-07-12</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>13</td>\n      <td>张十五</td>\n      <td>25</td>\n      <td>男</td>\n      <td>3</td>\n      <td>950</td>\n      <td>感冒</td>\n      <td>感冒药</td>\n      <td>休息</td>\n      <td>2023-07-13</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>14</td>\n      <td>李十六</td>\n      <td>28</td>\n      <td>女</td>\n      <td>2</td>\n      <td>650</td>\n      <td>发热</td>\n      <td>退烧药</td>\n      <td>休息</td>\n      <td>2023-07-14</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>15</td>\n      <td>王十七</td>\n      <td>58</td>\n      <td>男</td>\n      <td>1</td>\n      <td>1300</td>\n      <td>高血压</td>\n      <td>降压药</td>\n      <td>定期运动</td>\n      <td>2023-07-15</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"C:\\\\Users\\\\Administrator\\\\Desktop\\\\Python数据分析\\\\月考题\\\\大数据 大数据系 专高5 《Python数据分析EDA》月考题库（修改2）\\\\3-2 大数据 大数据系 专高5 《Python数据分析EDA》月考题库（新建）-已入库\\\\3-2 大数据 大数据系 专高5 《Python数据分析EDA》月考题库（新建）-已入库\\\\02-02-5-00001\\\\02-02-5-00001\\\\medical_data.csv\"\n",
    "\t\t\t\t ,encoding=\"GBK\")\n",
    "df"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "result = df.groupby(by=\"性别\")[\"患者ID\"].count()\n",
    "plt.pie(result,labels=[\"女\",\"男\"],autopct=\"%1.1f%%\")\n",
    "plt.title(\"男女患者分布图\")\n",
    "plt.legend()\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "outputs": [
    {
     "data": {
      "text/plain": "Text(0, 0.5, 'count')"
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "age = df[\"年龄\"]\n",
    "plt.hist(age)\n",
    "plt.title(\"年龄\")\n",
    "plt.xlabel(\"age\")\n",
    "plt.ylabel(\"count\")"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "source": [
    "money = df[\"医疗费用\"]\n",
    "money\n",
    "plt.boxplot(money)\n",
    "plt.xlabel(\"medical cost\")\n",
    "plt.show()\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "execution_count": 36,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "outputs": [
    {
     "data": {
      "text/plain": "Text(0, 0.5, 'medical cost')"
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "result = df.groupby(\"性别\")[\"医疗费用\"].mean()\n",
    "plt.bar(result.index,result.values)\n",
    "\n",
    "# for i in result.index:\n",
    "# \tplt.text(\n",
    "# \tx = i,\n",
    "# \ty = result[i],\n",
    "# \ts=result[i]\n",
    "# )\n",
    "plt.title(\"medical cost\")\n",
    "plt.xlabel(\"gender\")\n",
    "plt.ylabel(\"medical cost\")\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "outputs": [
    {
     "data": {
      "text/plain": "    患者ID   姓名  年龄 性别  就诊次数  医疗费用   诊断    药物   治疗方案        入院日期 age_box\n0      1   张三  45  男     3   500   感冒   感冒药     休息  2023-07-01     青年人\n1      2   李四  32  女     2   700   发热   退烧药     休息  2023-07-02     青年人\n2      3   王五  60  男     1  1200  高血压   降压药   定期运动  2023-07-03     青年人\n3      4   赵六  28  女     4   800   感冒   感冒药     休息  2023-07-04     年轻人\n4      5   刘七  50  男     2   600   胃炎   抗酸药   清淡饮食  2023-07-05     青年人\n5      6   陈八  65  女     1  1500  糖尿病   胰岛素   控制饮食  2023-07-06     老年人\n6      7   张九  38  男     3   900   头痛   止痛药     休息  2023-07-07     青年人\n7      8   李十  22  女     2   400   流感  抗病毒药     休息  2023-07-08     年轻人\n8      9  王十一  55  男     1  1000  高血压   降压药   定期运动  2023-07-09     青年人\n9     10  赵十二  30  女     4   750   过敏  抗过敏药  避免过敏源  2023-07-10     年轻人\n10    11  刘十三  40  男     2   550   胃炎   抗酸药   清淡饮食  2023-07-11     青年人\n11    12  陈十四  70  女     1  1800  糖尿病   胰岛素   控制饮食  2023-07-12     老年人\n12    13  张十五  25  男     3   950   感冒   感冒药     休息  2023-07-13     年轻人\n13    14  李十六  28  女     2   650   发热   退烧药     休息  2023-07-14     年轻人\n14    15  王十七  58  男     1  1300  高血压   降压药   定期运动  2023-07-15     青年人",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>患者ID</th>\n      <th>姓名</th>\n      <th>年龄</th>\n      <th>性别</th>\n      <th>就诊次数</th>\n      <th>医疗费用</th>\n      <th>诊断</th>\n      <th>药物</th>\n      <th>治疗方案</th>\n      <th>入院日期</th>\n      <th>age_box</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1</td>\n      <td>张三</td>\n      <td>45</td>\n      <td>男</td>\n      <td>3</td>\n      <td>500</td>\n      <td>感冒</td>\n      <td>感冒药</td>\n      <td>休息</td>\n      <td>2023-07-01</td>\n      <td>青年人</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2</td>\n      <td>李四</td>\n      <td>32</td>\n      <td>女</td>\n      <td>2</td>\n      <td>700</td>\n      <td>发热</td>\n      <td>退烧药</td>\n      <td>休息</td>\n      <td>2023-07-02</td>\n      <td>青年人</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>3</td>\n      <td>王五</td>\n      <td>60</td>\n      <td>男</td>\n      <td>1</td>\n      <td>1200</td>\n      <td>高血压</td>\n      <td>降压药</td>\n      <td>定期运动</td>\n      <td>2023-07-03</td>\n      <td>青年人</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>4</td>\n      <td>赵六</td>\n      <td>28</td>\n      <td>女</td>\n      <td>4</td>\n      <td>800</td>\n      <td>感冒</td>\n      <td>感冒药</td>\n      <td>休息</td>\n      <td>2023-07-04</td>\n      <td>年轻人</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>5</td>\n      <td>刘七</td>\n      <td>50</td>\n      <td>男</td>\n      <td>2</td>\n      <td>600</td>\n      <td>胃炎</td>\n      <td>抗酸药</td>\n      <td>清淡饮食</td>\n      <td>2023-07-05</td>\n      <td>青年人</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>6</td>\n      <td>陈八</td>\n      <td>65</td>\n      <td>女</td>\n      <td>1</td>\n      <td>1500</td>\n      <td>糖尿病</td>\n      <td>胰岛素</td>\n      <td>控制饮食</td>\n      <td>2023-07-06</td>\n      <td>老年人</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>7</td>\n      <td>张九</td>\n      <td>38</td>\n      <td>男</td>\n      <td>3</td>\n      <td>900</td>\n      <td>头痛</td>\n      <td>止痛药</td>\n      <td>休息</td>\n      <td>2023-07-07</td>\n      <td>青年人</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>8</td>\n      <td>李十</td>\n      <td>22</td>\n      <td>女</td>\n      <td>2</td>\n      <td>400</td>\n      <td>流感</td>\n      <td>抗病毒药</td>\n      <td>休息</td>\n      <td>2023-07-08</td>\n      <td>年轻人</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>9</td>\n      <td>王十一</td>\n      <td>55</td>\n      <td>男</td>\n      <td>1</td>\n      <td>1000</td>\n      <td>高血压</td>\n      <td>降压药</td>\n      <td>定期运动</td>\n      <td>2023-07-09</td>\n      <td>青年人</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>10</td>\n      <td>赵十二</td>\n      <td>30</td>\n      <td>女</td>\n      <td>4</td>\n      <td>750</td>\n      <td>过敏</td>\n      <td>抗过敏药</td>\n      <td>避免过敏源</td>\n      <td>2023-07-10</td>\n      <td>年轻人</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>11</td>\n      <td>刘十三</td>\n      <td>40</td>\n      <td>男</td>\n      <td>2</td>\n      <td>550</td>\n      <td>胃炎</td>\n      <td>抗酸药</td>\n      <td>清淡饮食</td>\n      <td>2023-07-11</td>\n      <td>青年人</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>12</td>\n      <td>陈十四</td>\n      <td>70</td>\n      <td>女</td>\n      <td>1</td>\n      <td>1800</td>\n      <td>糖尿病</td>\n      <td>胰岛素</td>\n      <td>控制饮食</td>\n      <td>2023-07-12</td>\n      <td>老年人</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>13</td>\n      <td>张十五</td>\n      <td>25</td>\n      <td>男</td>\n      <td>3</td>\n      <td>950</td>\n      <td>感冒</td>\n      <td>感冒药</td>\n      <td>休息</td>\n      <td>2023-07-13</td>\n      <td>年轻人</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>14</td>\n      <td>李十六</td>\n      <td>28</td>\n      <td>女</td>\n      <td>2</td>\n      <td>650</td>\n      <td>发热</td>\n      <td>退烧药</td>\n      <td>休息</td>\n      <td>2023-07-14</td>\n      <td>年轻人</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>15</td>\n      <td>王十七</td>\n      <td>58</td>\n      <td>男</td>\n      <td>1</td>\n      <td>1300</td>\n      <td>高血压</td>\n      <td>降压药</td>\n      <td>定期运动</td>\n      <td>2023-07-15</td>\n      <td>青年人</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bins=[0,30,60,100]\n",
    "lables=['年轻人','青年人','老年人']\n",
    "df[\"age_box\"] = pd.cut(df[\"年龄\"],bins=bins,labels=lables)\n",
    "df"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "result1 = df.groupby(by=[\"age_box\"])[\"诊断\"].count()\n",
    "plt.bar(result1.index,result1.values)\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "result2 = df.groupby(by=[\"诊断\"])[\"医疗费用\"].mean()\n",
    "plt.bar(result2.index,result2.values)\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "outputs": [
    {
     "data": {
      "text/plain": "     治疗方案\n诊断       \n发热      2\n头痛      1\n感冒      3\n流感      1\n糖尿病     2\n胃炎      2\n过敏      1\n高血压     3",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>治疗方案</th>\n    </tr>\n    <tr>\n      <th>诊断</th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>发热</th>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>头痛</th>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>感冒</th>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>流感</th>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>糖尿病</th>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>胃炎</th>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>过敏</th>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>高血压</th>\n      <td>3</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result3 = df.groupby(by=\"诊断\")[[\"治疗方案\"]].count()\n",
    "result3"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "outputs": [
    {
     "data": {
      "text/plain": "     治疗方案\n诊断       \n感冒      3\n高血压     3",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>治疗方案</th>\n    </tr>\n    <tr>\n      <th>诊断</th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>感冒</th>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>高血压</th>\n      <td>3</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num = result3.max().values[0]\n",
    "result3.query(\"治疗方案==@num\")\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "outputs": [
    {
     "data": {
      "text/plain": "0     2023\n1     2023\n2     2023\n3     2023\n4     2023\n5     2023\n6     2023\n7     2023\n8     2023\n9     2023\n10    2023\n11    2023\n12    2023\n13    2023\n14    2023\nName: 入院日期, dtype: int64"
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"入院日期\"] = pd.to_datetime(df[\"入院日期\"])\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "outputs": [
    {
     "data": {
      "text/plain": "    患者ID   姓名  年龄 性别  就诊次数  医疗费用   诊断    药物   治疗方案       入院日期 age_box  month\n0      1   张三  45  男     3   500   感冒   感冒药     休息 2023-07-01     青年人      7\n1      2   李四  32  女     2   700   发热   退烧药     休息 2023-07-02     青年人      7\n2      3   王五  60  男     1  1200  高血压   降压药   定期运动 2023-07-03     青年人      7\n3      4   赵六  28  女     4   800   感冒   感冒药     休息 2023-07-04     年轻人      7\n4      5   刘七  50  男     2   600   胃炎   抗酸药   清淡饮食 2023-07-05     青年人      7\n5      6   陈八  65  女     1  1500  糖尿病   胰岛素   控制饮食 2023-07-06     老年人      7\n6      7   张九  38  男     3   900   头痛   止痛药     休息 2023-07-07     青年人      7\n7      8   李十  22  女     2   400   流感  抗病毒药     休息 2023-07-08     年轻人      7\n8      9  王十一  55  男     1  1000  高血压   降压药   定期运动 2023-07-09     青年人      7\n9     10  赵十二  30  女     4   750   过敏  抗过敏药  避免过敏源 2023-07-10     年轻人      7\n10    11  刘十三  40  男     2   550   胃炎   抗酸药   清淡饮食 2023-07-11     青年人      7\n11    12  陈十四  70  女     1  1800  糖尿病   胰岛素   控制饮食 2023-07-12     老年人      7\n12    13  张十五  25  男     3   950   感冒   感冒药     休息 2023-07-13     年轻人      7\n13    14  李十六  28  女     2   650   发热   退烧药     休息 2023-07-14     年轻人      7\n14    15  王十七  58  男     1  1300  高血压   降压药   定期运动 2023-07-15     青年人      7",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>患者ID</th>\n      <th>姓名</th>\n      <th>年龄</th>\n      <th>性别</th>\n      <th>就诊次数</th>\n      <th>医疗费用</th>\n      <th>诊断</th>\n      <th>药物</th>\n      <th>治疗方案</th>\n      <th>入院日期</th>\n      <th>age_box</th>\n      <th>month</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1</td>\n      <td>张三</td>\n      <td>45</td>\n      <td>男</td>\n      <td>3</td>\n      <td>500</td>\n      <td>感冒</td>\n      <td>感冒药</td>\n      <td>休息</td>\n      <td>2023-07-01</td>\n      <td>青年人</td>\n      <td>7</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2</td>\n      <td>李四</td>\n      <td>32</td>\n      <td>女</td>\n      <td>2</td>\n      <td>700</td>\n      <td>发热</td>\n      <td>退烧药</td>\n      <td>休息</td>\n      <td>2023-07-02</td>\n      <td>青年人</td>\n      <td>7</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>3</td>\n      <td>王五</td>\n      <td>60</td>\n      <td>男</td>\n      <td>1</td>\n      <td>1200</td>\n      <td>高血压</td>\n      <td>降压药</td>\n      <td>定期运动</td>\n      <td>2023-07-03</td>\n      <td>青年人</td>\n      <td>7</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>4</td>\n      <td>赵六</td>\n      <td>28</td>\n      <td>女</td>\n      <td>4</td>\n      <td>800</td>\n      <td>感冒</td>\n      <td>感冒药</td>\n      <td>休息</td>\n      <td>2023-07-04</td>\n      <td>年轻人</td>\n      <td>7</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>5</td>\n      <td>刘七</td>\n      <td>50</td>\n      <td>男</td>\n      <td>2</td>\n      <td>600</td>\n      <td>胃炎</td>\n      <td>抗酸药</td>\n      <td>清淡饮食</td>\n      <td>2023-07-05</td>\n      <td>青年人</td>\n      <td>7</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>6</td>\n      <td>陈八</td>\n      <td>65</td>\n      <td>女</td>\n      <td>1</td>\n      <td>1500</td>\n      <td>糖尿病</td>\n      <td>胰岛素</td>\n      <td>控制饮食</td>\n      <td>2023-07-06</td>\n      <td>老年人</td>\n      <td>7</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>7</td>\n      <td>张九</td>\n      <td>38</td>\n      <td>男</td>\n      <td>3</td>\n      <td>900</td>\n      <td>头痛</td>\n      <td>止痛药</td>\n      <td>休息</td>\n      <td>2023-07-07</td>\n      <td>青年人</td>\n      <td>7</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>8</td>\n      <td>李十</td>\n      <td>22</td>\n      <td>女</td>\n      <td>2</td>\n      <td>400</td>\n      <td>流感</td>\n      <td>抗病毒药</td>\n      <td>休息</td>\n      <td>2023-07-08</td>\n      <td>年轻人</td>\n      <td>7</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>9</td>\n      <td>王十一</td>\n      <td>55</td>\n      <td>男</td>\n      <td>1</td>\n      <td>1000</td>\n      <td>高血压</td>\n      <td>降压药</td>\n      <td>定期运动</td>\n      <td>2023-07-09</td>\n      <td>青年人</td>\n      <td>7</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>10</td>\n      <td>赵十二</td>\n      <td>30</td>\n      <td>女</td>\n      <td>4</td>\n      <td>750</td>\n      <td>过敏</td>\n      <td>抗过敏药</td>\n      <td>避免过敏源</td>\n      <td>2023-07-10</td>\n      <td>年轻人</td>\n      <td>7</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>11</td>\n      <td>刘十三</td>\n      <td>40</td>\n      <td>男</td>\n      <td>2</td>\n      <td>550</td>\n      <td>胃炎</td>\n      <td>抗酸药</td>\n      <td>清淡饮食</td>\n      <td>2023-07-11</td>\n      <td>青年人</td>\n      <td>7</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>12</td>\n      <td>陈十四</td>\n      <td>70</td>\n      <td>女</td>\n      <td>1</td>\n      <td>1800</td>\n      <td>糖尿病</td>\n      <td>胰岛素</td>\n      <td>控制饮食</td>\n      <td>2023-07-12</td>\n      <td>老年人</td>\n      <td>7</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>13</td>\n      <td>张十五</td>\n      <td>25</td>\n      <td>男</td>\n      <td>3</td>\n      <td>950</td>\n      <td>感冒</td>\n      <td>感冒药</td>\n      <td>休息</td>\n      <td>2023-07-13</td>\n      <td>年轻人</td>\n      <td>7</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>14</td>\n      <td>李十六</td>\n      <td>28</td>\n      <td>女</td>\n      <td>2</td>\n      <td>650</td>\n      <td>发热</td>\n      <td>退烧药</td>\n      <td>休息</td>\n      <td>2023-07-14</td>\n      <td>年轻人</td>\n      <td>7</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>15</td>\n      <td>王十七</td>\n      <td>58</td>\n      <td>男</td>\n      <td>1</td>\n      <td>1300</td>\n      <td>高血压</td>\n      <td>降压药</td>\n      <td>定期运动</td>\n      <td>2023-07-15</td>\n      <td>青年人</td>\n      <td>7</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"month\"] = df[\"入院日期\"].dt.month\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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9Pt+QqAEAAInL1ZWUxsZGlZeXR5e9Xq88Ho+SkpLU0dGh9evXq6amZshHONezbNkyNTc3R5dbW1u1YMECNyMBAIAE5SpS8vLyVFtbq9raWnV2dmrz5s1auXKlpk2bpsLCQn3ta19TcXGxLl++rMuXL8sYI+nTe08GBgaG7a+oqEivv/66Xn31VQ0MDOjZZ5/VqlWrxufIAADAlOYqUubNm6f6+npVV1dr8eLF6u/v18GDB3X06FGdPn1ae/fu1axZs6KP8+fPS/r0HpaGhoZh+0tPT1dlZaXWrFmjjIwMnTlzRlu3bh2fIwMAAFOax1y93DGJOjo61N7eruXLl2vmzJljfp3jOEpNTVU4HJbf74/jhAAAYLyM9f07phtnx1t2drays7MnewwAAGAR/hdkAABgJSIFAABYiUgBAABWIlIAAICViBQAAGAlIgUAAFiJSAEAAFYiUgAAgJWIFAAAYCUiBQAAWIlIAQAAViJSAACAlYgUAABgJSIFAABYiUgBAABWIlIAAICViBQAAGAlIgUAAFiJSAEAAFYiUgAAgJWIFAAAYCUiBQAAWIlIAQAAViJSAACAlYgUAABgJSIFAABYiUgBAABWIlIAAICViBQAAGAlIgUAAFiJSAEAAFYiUgAAgJWIFAAAYCUiBQAAWIlIAQAAViJSAACAlYgUAABgJSIFAABYiUgBAABWiilSent71dLSop6envGeBwAAQFIMkVJXV6esrCyVlJQoMzNTdXV10ee6u7uVnZ2t9957b8z7KyoqksfjiT7uv/9+tyMBAIAElOxm43A4rLKyMjU1NSkYDGr//v0qLy/Xww8/rO7ubhUWFroKFEk6efKkTp06pczMTEnStGnTXL0eAAAkJldXUhzHUVVVlYLBoCSpoKBAly5dkiStW7dOjz76qKsffuHCBRljdOeddyotLU1paWmaMWOGq30AAIDE5CpSAoGANmzYIEkaGBhQZWWliouLJUl79+7V448/7uqHv/nmmxocHFRmZqZmzJihdevWcZ8LAACQFOONs6FQSHPnztWRI0e0e/duSVJ2drbr/bS3t+vuu+9WQ0ODTpw4oY6ODlVUVIy4fSQSkeM4Qx4AACAxeYwxxu2LjDF6++23tXHjRs2ZM0f19fX/f4cejzo6OpSVleV6mKamJq1du1bd3d3XfH779u3asWPHsPXhcFh+v9/1zwMAABPPcRylpqaO+v4dU6Rc1dHRoZycHH344YdKS0v7dIefIVLa29uVn5+vK1euyOfzDXs+EokoEolElx3HUSAQIFIAAJhCxhoprj7uaWxsVHl5eXTZ6/XK4/EoKSm23wn3yCOP6Pjx49Hl5uZmZWRkXDNQJMnn88nv9w95AACAxOTqK8h5eXmqra1Vbm6uVq9era1bt2rlypWjxoLjOEpJSRn29eK77rpLGzduVGVlpbq7u1VRUaHS0lL3RwEAABKOq0sg8+bNU319vaqrq7V48WL19/fr4MGDo74uGAyqoaFh2PpNmzYpGAzqgQceUGlpqcrKyrRlyxY3IwEAgAT1me5JmWxj/UwLAADYIy73pAAAAEwUIgUAAFiJSAEAAFYiUgAAgJWIFAAAYCUiBQAAWIlIAQAAViJSAACAlYgUAABgJSIFAABYiUgBAABWIlIAAICViBQAAGAlIgUAAFiJSAEAAFYiUgAAgJWIFAAAYCUiBQAAWIlIAQAAViJSAACAlYgUAABgJSIFAABYiUgBAABWIlIAAICViBQAAGAlIgUAAFiJSAEAAFYiUgAAgJWIFAAAYCUiBQAAWIlIAQAAViJSAACAlYgUAABgJSIFAABYiUgBAABWIlIAAICViBQAAGAlIgUAAFiJSAEAAFYiUgAAgJWIFAAAYKWYIqW3t1ctLS3q6ekZ73kAAAAkxRApdXV1ysrKUklJiTIzM1VXVxd9rru7W9nZ2XrvvffGvL/Gxkbl5+crPT1du3btcjsOAABIUK4iJRwOq6ysTE1NTTp16pRqampUXl4u6dNAKSwsdBUoXV1dKioq0vr169Xc3KxDhw7p2LFjrg4AAAAkJleR4jiOqqqqFAwGJUkFBQW6dOmSJGndunV69NFHXf3wQ4cOaf78+XrqqaeUm5urbdu2ad++fa72AQAAEpOrSAkEAtqwYYMkaWBgQJWVlSouLpYk7d27V48//rirHx4KhXTffffJ4/FIku655x699dZbI24fiUTkOM6QBwAASEzJsbwoFAppxYoV8nq9amtrkyRlZ2e73o/jOFq0aFF02e/36+LFiyNuv3PnTu3YscP9wAAAYMqJ6ds9wWBQR48eVW5urkpKSmL+4cnJyfL5fNHl6dOnq7+/f8TtKyoqFA6Ho4/Ozs6YfzYAALBbTFdSPB6Pli5dqgMHDignJ0e9vb1KS0tzvZ/Zs2erq6srutzX1yev1zvi9j6fb0jUAACAxOXqSkpjY2P02zyS5PV65fF4lJQU2++EW7ZsmZqbm6PLra2tWrBgQUz7AgAAicVVXeTl5am2tla1tbXq7OzU5s2btXLlSvn9/uu+znEcDQwMDFtfVFSk119/Xa+++qoGBgb07LPPatWqVe6OAAAAJCRXkTJv3jzV19erurpaixcvVn9/vw4ePDjq64LBoBoaGoatT09PV2VlpdasWaOMjAydOXNGW7dudTMSAABIUB5jjJnsITo6OtTe3q7ly5dr5syZY36d4zhKTU1VOBwe9WoOAACww1jfv2O6cXa8ZWdnx/QVZgAAkLj4X5ABAICViBQAAGAlIgUAAFiJSAEAAFYiUgAAgJWIFAAAYCUiBQAAWIlIAQAAViJSAACAlYgUAABgJSIFAABYiUgBAABWIlIAAICViBQAAGAlIgUAAFiJSAEAAFYiUgAAgJWIFAAAYCUiBQAAWIlIAQAAViJSAACAlYgUAABgJSIFAABYiUgBAABWIlIAAICViBQAAGAlIgUAAFiJSAEAAFYiUgAAgJWIFAAAYCUiBQAAWIlIAQAAViJSAACAlYgUAABgJSIFAABYiUgBAABWIlIAAICViBQAAGAlIgUAAFiJSAEAAFaKKVJ6e3vV0tKinp6e8Z4HAABAUgyRUldXp6ysLJWUlCgzM1N1dXWSpHfeeUfLli3T5z73OZWXl8sYM6b9BYNBeTye6KOkpMTtSAAAIAG5ipRwOKyysjI1NTXp1KlTqqmpUXl5uSKRiB566CEtXbpUJ0+e1OnTp7V///5R99ff369z587pgw8+UE9Pj3p6evTiiy/GeiwAACCBuIoUx3FUVVWlYDAoSSooKNClS5f085//XOFwWLt27VJOTo6+973vad++faPur7W1VcFgULfeeqvS0tKUlpamlJSU2I4EAAAkFFeREggEtGHDBknSwMCAKisrVVxcrFAopHvvvVc333yzpE8/wjl9+vSo+3vzzTf1/vvvRyOltLRUkUhkxO0jkYgcxxnyAAAAiSmmG2dDoZDmzp2rI0eOaPfu3XIcR9nZ2dHnPR6PbrrpplFvrD1z5oy+8pWv6Pjx4/rFL36hX/7yl6qsrBxx+507dyo1NTX6CAQCsYwPAACmAI8Z6x2u/4sxRm+//bY2btyoOXPmKCcnRwMDA9q1a1d0m0AgoBMnTmjBggVj3u/Bgwe1e/dunTx58prPRyKRIVdaHMdRIBBQOByW3+93exgAAGASOI6j1NTUUd+/Y7qS4vF4tHTpUh04cEA//vGPNXv2bHV1dQ3Zpq+vT16v19V+58yZowsXLoz4vM/nk9/vH/IAAACJyVWkNDY2qry8PLrs9Xrl8XiUn5+v5ubm6PqOjg5FIhHNnj37uvv70pe+pM7Ozuhyc3Ozbr/9djcjAQCABOUqUvLy8lRbW6va2lp1dnZq8+bNWrlypdasWSPHcfTSSy9Jkr73ve/p/vvv10033STp01/+Njg4OGx/ixcv1l/8xV+opaVFBw4c0AsvvKDS0tJxOCwAADDVub4n5Ze//KWeeOIJdXZ2atWqVfrBD36gW2+9VT/96U+1fv16paSkKCkpSa+99poWLVr06Q/xeNTa2qolS5YM2Vdvb68ee+wx/eIXv9CcOXO0adMmV5Ey1s+0AACAPcb6/h3TjbMj+e1vf6u33npL9957r2655Zbx2u2IiBQAAKaesb5/J4/nD507d64efPDB8dwlAAC4QfG/IAMAACsRKQAAwEpECgAAsBKRAgAArESkAAAAKxEpAADASkQKAACwEpECAACsRKQAAAArESkAAMBKRAoAALASkQIAAKxEpAAAACsRKQAAwEpECgAAsBKRAgAArESkAAAAKxEpAADASsmTPcBnYYyRJDmOM8mTAACAsbr6vn31fXwkUzpS+vr6JEmBQGCSJwEAAG719fUpNTV1xOc9ZrSMsdgnn3yiixcvatasWfJ4PJM9zrhxHEeBQECdnZ3y+/2TPc6kuNHPwY1+/BLngOO/sY9fSuxzYIxRX1+f5s+fr6Skke88mdJXUpKSkpSZmTnZY8SN3+9PuD+Ybt3o5+BGP36Jc8Dx39jHLyXuObjeFZSruHEWAABYiUgBAABWIlIs5PP59PTTT8vn8032KJPmRj8HN/rxS5wDjv/GPn6JcyBN8RtnAQBA4uJKCgAAsBKRAgAArESkAAAwhfznf/6nTp48qY8//niyR4k7ImUSbdq0SQ899NCo223fvl0ej2fY47XXXov/kHE21nMgSd/5zneUkZGhmTNnqqioSN3d3XGeLv7GevzGGD377LPKzc1Venq6/uqv/kr/8z//MwETIh72799/zb/T+/fvH/W1b7zxhj7/+c/Hf8g4i/Uc7NixQ7Nnz5bP51NxcXH0N49PNbEe/7e//W0VFBTo0UcfVXZ2ttrb2ydm4MliMClCoZCZOXOmOXfu3KjbfvTRR6anpyf6+PWvf21uvfVW09vbOwGTxo+bc9DY2GgWL15s2tvbzbvvvmvWrFlj/vRP/3QCpowfN8e/d+9eM3/+fNPS0mLa29vN7//+75s/+ZM/mYAp4+Oll14ykoY9Xnrppeu+rq6uztx2221m3rx55uWXX56YYeMgEokM+Tvd2dlp0tPTzdmzZ6/7upMnT5o5c+aY22+/fWIGjaNYzsEPf/hDk5uba1paWsy7775rPv/5z5vNmzdP4NTjJ5bjP3bsmMnNzTXhcNgYY8w3vvEN82d/9mcTNPHkIFImweDgoPniF79onnrqqZhe/81vftN897vfHeepJpbbc/Dcc8+Z8vLy6PIPf/hD86UvfSle48Wd2+Nfvny5ef7556PLDQ0NZtasWfEaL+5i+Qf61KlTxuv1mr1795rf/OY35o477jDt7e0TOHX8fPe73zXf/OY3r7vN5cuXzW233Wb+7u/+LiEi5f8ayznYuXOneeONN6LL27ZtM6tXr473aBNiLMf/xhtvmNdeey26XF1dbQoLC+M92qQiUiZBTU2Nufnmm82+ffvM4cOHTSQSGfNrL1y4YNLT001fX18cJ4w/t+fgn/7pn8wdd9xhzp07Z/77v//b3HfffWbbtm0TNO34c3v8+fn55pVXXokuHzlyxKSlpcV7zAkzln+g/+Zv/sasWrUqulxVVWW2bNkS79Hi7qOPPjJz5swxHR0d190uEomY999/3xw7dizhImWs5+D/euSRR8zjjz8en6EmUCzH39XVZe6++26zb9+++A1mAe5JmWCXL1/W008/rYULF+r8+fOqrKzUV77yFX300Udjev2ePXu0fv16zZw5M86Txk8s52D16tXKyclRTk6OMjIydPnyZT355JMTOPX4ieX4CwoKdPjw4ejy/v379Ud/9EcTMW7cXblyRdXV1dq8efN1twuFQlqxYkV0+Z577tFbb70V7/Hi7uWXX9YXv/hFZWVlXXc7r9erBQsWTMxQE2ys5+B/+/d//3f95Cc/0be+9a34DTZB3B7/3r17ddttt2nu3Ln68z//8/gON9kmu5JuNAcOHDApKSmmq6vLGGPMwMCA+cIXvmD+8R//cdTX/u53vzNz5841//Zv/xbvMeMqlnNQV1dn8vPzzenTp80HH3xgvvGNb5i1a9dO1MjjKpbjP3/+vFm0aJH58pe/bO666y4jyTQ1NU3UyHG1b98+89BDD426XUFBwZCrSe+8844JBoPxHG1CLFu2zDQ0NIx5+0S8kuL2HAwODpo/+IM/MGVlZXGcauK4Pf4rV66Yn/3sZyYzM9O8+OKLcZxs8k3p/wV5Knr//fd17733Kj09XZKUnJysYDCos2fPjvraY8eO6ZZbbtGiRYviPWZcxXIODh06pNLSUuXn50uSqqqqlJaWpt7eXqWlpU3E2OMmluO/7bbb9M4776i9vV1/+7d/q7lz52r58uUTNXJc7dmzR9u3bx91u+Tk5CG/Hnz69Onq7++P42Txd/bsWZ09ezZhrorFIpZz8J3vfEcffvihnnvuuThONjFiOX6fz6fCwkJ1dXVp9+7d+uu//us4Tji5+LhngmVmZg67rH/+/PkxXcZ95ZVXtHbt2niNNmFiOQeffPKJPvjgg+jyb3/7W0nS4OBgfIaMo1j/DHg8Hvn9fr366qv6/ve/H88RJ4ybf6Bnz56trq6u6HJfX5+8Xm88x4u7V155RYWFhZo2bdpkjzJp3J6Dn/3sZ9q1a5d+9KMf6eabb47zdPHn5virq6v18ssvR5e9Xq9uuummeI436YiUCfbggw/q9OnT2rNnj95//33t3r1boVBIa9euleM4GhgYGPG1R44c0R/+4R9O3LBxEss5WL58uWpra7Vnzx4dOHBA69at05e//GXdcsstk3AEn81n+TPw93//93r44Yf1e7/3exM4cfy4+Qd62bJlam5uji63trZO+Xs0rvV3ure3d0rGd6zcnIO2tjatX79eL774ogKBgC5fvjzlr6a5Of6FCxfqiSee0LFjx3TmzBk999xzevjhhydo0kky2Z833YiOHz9u7r33XpOSkmIWLlxofvrTnxpjjLn99tvNT37yk2u+5uzZs+amm26a8t/qucrtObhy5Yp5/PHHzfz5843X6zVf/epXzX/8x39M8NTjJ5Y/A++++67x+/2ms7NzAieNr+XLlw/7dkJPT4/53e9+N2zbX//612bGjBnmN7/5jenr6zNLliwZ8rXsqaa/v994vV7T1tY2ZL0k09raOuLrEumeFLfn4Iknnhj2u3Wm8rmI5c/ACy+8YObNm2fS09PNk08+aQYHBydg0snD/4IMYFJ89NFHSktLUygU0he+8IXoeo/Ho9bWVi1ZsmTYa7Zs2aLnn39e06dPV25urv7lX/5FKSkpEzg1gIlEpACYUk6fPq0LFy7oq1/96pS/JwXA9REpAADAStw4CwAArESkAAAAKxEpAADASkQKAACwEpECAACsRKQAAAArESkAAMBKRAoAALASkQIAAKz0/wCcP1nOpKOZpgAAAABJRU5ErkJggg=="
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "result4 = df.groupby(\"month\")[\"就诊次数\"].sum()\n",
    "plt.plot(result4.index,result4.values)\n",
    "plt.show()\n",
    "\n",
    "plt.scatter(result4.index,result4.values)\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i in df.index:\n",
    "\tif df.loc[i].性别 == \"男\":\n",
    "\t\tplt.scatter(df.loc[i].就诊次数,df.loc[i].医疗费用,c=\"green\")\n",
    "\telse:\n",
    "\t\tplt.scatter(df.loc[i].就诊次数,df.loc[i].医疗费用,c=\"red\")"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "outputs": [],
   "source": [
    "result5 = df.groupby([\"治疗方案\",\"药物\"])[\"医疗费用\"].mean()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for index,value in enumerate(result5.index):\n",
    "\tplt.bar(\"-\".join(value),result5.values[index])\n",
    "\n",
    "#  把X轴设置成45度\n",
    "plt.xticks(rotation=-45)\n",
    "plt.show()\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "outputs": [
    {
     "data": {
      "text/plain": "诊断   治疗方案 \n发热   休息       2\n头痛   休息       1\n感冒   休息       3\n流感   休息       1\n糖尿病  控制饮食     2\n胃炎   清淡饮食     2\n过敏   避免过敏源    1\n高血压  定期运动     3\nName: 治疗方案, dtype: int64"
     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby([\"诊断\",\"治疗方案\"])[\"治疗方案\"].count()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "color = np.random.randn(df.value_counts([\"诊断\"]).count())\n",
    "\n",
    "\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "d = {\n",
    "\t\"感冒\":\"red\",\n",
    "\t\"高血压\":\"green\",\n",
    "\t\"发热\":\"pink\",\n",
    "\t\"糖尿病\":\"yellow\",\n",
    "\t\"胃炎\":\"white\",\n",
    "\t\"头痛\":\"black\",\n",
    "\t\"流感\":\"red\",\n",
    "\t\"过敏\":\"red\",\n",
    "}\n",
    "for index,row in enumerate(df.iterrows()):\n",
    "\tplt.scatter(row[1].就诊次数,row[1].医疗费用,c=d[row[1].诊断])\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "outputs": [
    {
     "data": {
      "text/plain": "    患者ID   姓名  年龄 性别  就诊次数  医疗费用   诊断    药物   治疗方案       入院日期 age_box  month  \\\n0      1   张三  45  男     3   500   感冒   感冒药     休息 2023-07-01     青年人      7   \n1      2   李四  32  女     2   700   发热   退烧药     休息 2023-07-02     青年人      7   \n2      3   王五  60  男     1  1200  高血压   降压药   定期运动 2023-07-03     青年人      7   \n3      4   赵六  28  女     4   800   感冒   感冒药     休息 2023-07-04     年轻人      7   \n4      5   刘七  50  男     2   600   胃炎   抗酸药   清淡饮食 2023-07-05     青年人      7   \n5      6   陈八  65  女     1  1500  糖尿病   胰岛素   控制饮食 2023-07-06     老年人      7   \n6      7   张九  38  男     3   900   头痛   止痛药     休息 2023-07-07     青年人      7   \n7      8   李十  22  女     2   400   流感  抗病毒药     休息 2023-07-08     年轻人      7   \n8      9  王十一  55  男     1  1000  高血压   降压药   定期运动 2023-07-09     青年人      7   \n9     10  赵十二  30  女     4   750   过敏  抗过敏药  避免过敏源 2023-07-10     年轻人      7   \n10    11  刘十三  40  男     2   550   胃炎   抗酸药   清淡饮食 2023-07-11     青年人      7   \n11    12  陈十四  70  女     1  1800  糖尿病   胰岛素   控制饮食 2023-07-12     老年人      7   \n12    13  张十五  25  男     3   950   感冒   感冒药     休息 2023-07-13     年轻人      7   \n13    14  李十六  28  女     2   650   发热   退烧药     休息 2023-07-14     年轻人      7   \n14    15  王十七  58  男     1  1300  高血压   降压药   定期运动 2023-07-15     青年人      7   \n\n    weekday  \n0         6  \n1         7  \n2         1  \n3         2  \n4         3  \n5         4  \n6         5  \n7         6  \n8         7  \n9         1  \n10        2  \n11        3  \n12        4  \n13        5  \n14        6  ",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>患者ID</th>\n      <th>姓名</th>\n      <th>年龄</th>\n      <th>性别</th>\n      <th>就诊次数</th>\n      <th>医疗费用</th>\n      <th>诊断</th>\n      <th>药物</th>\n      <th>治疗方案</th>\n      <th>入院日期</th>\n      <th>age_box</th>\n      <th>month</th>\n      <th>weekday</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1</td>\n      <td>张三</td>\n      <td>45</td>\n      <td>男</td>\n      <td>3</td>\n      <td>500</td>\n      <td>感冒</td>\n      <td>感冒药</td>\n      <td>休息</td>\n      <td>2023-07-01</td>\n      <td>青年人</td>\n      <td>7</td>\n      <td>6</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2</td>\n      <td>李四</td>\n      <td>32</td>\n      <td>女</td>\n      <td>2</td>\n      <td>700</td>\n      <td>发热</td>\n      <td>退烧药</td>\n      <td>休息</td>\n      <td>2023-07-02</td>\n      <td>青年人</td>\n      <td>7</td>\n      <td>7</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>3</td>\n      <td>王五</td>\n      <td>60</td>\n      <td>男</td>\n      <td>1</td>\n      <td>1200</td>\n      <td>高血压</td>\n      <td>降压药</td>\n      <td>定期运动</td>\n      <td>2023-07-03</td>\n      <td>青年人</td>\n      <td>7</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>4</td>\n      <td>赵六</td>\n      <td>28</td>\n      <td>女</td>\n      <td>4</td>\n      <td>800</td>\n      <td>感冒</td>\n      <td>感冒药</td>\n      <td>休息</td>\n      <td>2023-07-04</td>\n      <td>年轻人</td>\n      <td>7</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>5</td>\n      <td>刘七</td>\n      <td>50</td>\n      <td>男</td>\n      <td>2</td>\n      <td>600</td>\n      <td>胃炎</td>\n      <td>抗酸药</td>\n      <td>清淡饮食</td>\n      <td>2023-07-05</td>\n      <td>青年人</td>\n      <td>7</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>6</td>\n      <td>陈八</td>\n      <td>65</td>\n      <td>女</td>\n      <td>1</td>\n      <td>1500</td>\n      <td>糖尿病</td>\n      <td>胰岛素</td>\n      <td>控制饮食</td>\n      <td>2023-07-06</td>\n      <td>老年人</td>\n      <td>7</td>\n      <td>4</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>7</td>\n      <td>张九</td>\n      <td>38</td>\n      <td>男</td>\n      <td>3</td>\n      <td>900</td>\n      <td>头痛</td>\n      <td>止痛药</td>\n      <td>休息</td>\n      <td>2023-07-07</td>\n      <td>青年人</td>\n      <td>7</td>\n      <td>5</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>8</td>\n      <td>李十</td>\n      <td>22</td>\n      <td>女</td>\n      <td>2</td>\n      <td>400</td>\n      <td>流感</td>\n      <td>抗病毒药</td>\n      <td>休息</td>\n      <td>2023-07-08</td>\n      <td>年轻人</td>\n      <td>7</td>\n      <td>6</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>9</td>\n      <td>王十一</td>\n      <td>55</td>\n      <td>男</td>\n      <td>1</td>\n      <td>1000</td>\n      <td>高血压</td>\n      <td>降压药</td>\n      <td>定期运动</td>\n      <td>2023-07-09</td>\n      <td>青年人</td>\n      <td>7</td>\n      <td>7</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>10</td>\n      <td>赵十二</td>\n      <td>30</td>\n      <td>女</td>\n      <td>4</td>\n      <td>750</td>\n      <td>过敏</td>\n      <td>抗过敏药</td>\n      <td>避免过敏源</td>\n      <td>2023-07-10</td>\n      <td>年轻人</td>\n      <td>7</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>11</td>\n      <td>刘十三</td>\n      <td>40</td>\n      <td>男</td>\n      <td>2</td>\n      <td>550</td>\n      <td>胃炎</td>\n      <td>抗酸药</td>\n      <td>清淡饮食</td>\n      <td>2023-07-11</td>\n      <td>青年人</td>\n      <td>7</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>12</td>\n      <td>陈十四</td>\n      <td>70</td>\n      <td>女</td>\n      <td>1</td>\n      <td>1800</td>\n      <td>糖尿病</td>\n      <td>胰岛素</td>\n      <td>控制饮食</td>\n      <td>2023-07-12</td>\n      <td>老年人</td>\n      <td>7</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>13</td>\n      <td>张十五</td>\n      <td>25</td>\n      <td>男</td>\n      <td>3</td>\n      <td>950</td>\n      <td>感冒</td>\n      <td>感冒药</td>\n      <td>休息</td>\n      <td>2023-07-13</td>\n      <td>年轻人</td>\n      <td>7</td>\n      <td>4</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>14</td>\n      <td>李十六</td>\n      <td>28</td>\n      <td>女</td>\n      <td>2</td>\n      <td>650</td>\n      <td>发热</td>\n      <td>退烧药</td>\n      <td>休息</td>\n      <td>2023-07-14</td>\n      <td>年轻人</td>\n      <td>7</td>\n      <td>5</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>15</td>\n      <td>王十七</td>\n      <td>58</td>\n      <td>男</td>\n      <td>1</td>\n      <td>1300</td>\n      <td>高血压</td>\n      <td>降压药</td>\n      <td>定期运动</td>\n      <td>2023-07-15</td>\n      <td>青年人</td>\n      <td>7</td>\n      <td>6</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 182,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"weekday\"] = df[\"入院日期\"].dt.weekday+1\n",
    "df"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "outputs": [
    {
     "data": {
      "text/plain": "<BarContainer object of 7 artists>"
     },
     "execution_count": 185,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": "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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "result6 = df.groupby(\"weekday\")[\"就诊次数\"].sum()\n",
    "\n",
    "plt.bar(result6.index,result6.values)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "outputs": [
    {
     "data": {
      "text/plain": "(array([1., 0., 0., 0., 0., 0., 0., 0., 0., 1.]),\n array([2.        , 2.02857143, 2.05714286, 2.08571429, 2.11428571,\n        2.14285714, 2.17142857, 2.2       , 2.22857143, 2.25714286,\n        2.28571429]),\n <BarContainer object of 10 artists>)"
     },
     "execution_count": 187,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": "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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "resul6 = df.groupby(\"性别\")[\"就诊次数\"].mean()\n",
    "plt.hist(resul6)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "outputs": [
    {
     "data": {
      "text/plain": "[<matplotlib.lines.Line2D at 0x1a654e016a0>]"
     },
     "execution_count": 191,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "result7 = df.groupby(\"age_box\")[\"就诊次数\"].mean()\n",
    "plt.plot(result7.index,result7.values)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "df[\"年龄\"] = df[\"年龄\"].map(lambda x: x if x <= 100 else np.nan)\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "outputs": [
    {
     "data": {
      "text/plain": "         就诊次数\n诊断           \n发热   2.000000\n头痛   3.000000\n感冒   3.333333\n流感   2.000000\n糖尿病  1.000000\n胃炎   2.000000\n过敏   4.000000\n高血压  1.000000",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>就诊次数</th>\n    </tr>\n    <tr>\n      <th>诊断</th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>发热</th>\n      <td>2.000000</td>\n    </tr>\n    <tr>\n      <th>头痛</th>\n      <td>3.000000</td>\n    </tr>\n    <tr>\n      <th>感冒</th>\n      <td>3.333333</td>\n    </tr>\n    <tr>\n      <th>流感</th>\n      <td>2.000000</td>\n    </tr>\n    <tr>\n      <th>糖尿病</th>\n      <td>1.000000</td>\n    </tr>\n    <tr>\n      <th>胃炎</th>\n      <td>2.000000</td>\n    </tr>\n    <tr>\n      <th>过敏</th>\n      <td>4.000000</td>\n    </tr>\n    <tr>\n      <th>高血压</th>\n      <td>1.000000</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 195,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result8 = df.groupby(\"诊断\")[[\"就诊次数\"]].mean()\n",
    "\n",
    "def fun(x):\n",
    "\tif x <= 1:\n",
    "\t\treturn 1\n",
    "\telif x >= 10:\n",
    "\t\treturn 10\n",
    "\treturn x\n",
    "result8[\"就诊次数\"] = result8[\"就诊次数\"].map(fun)\n",
    "result8"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "outputs": [
    {
     "data": {
      "text/plain": "<BarContainer object of 8 artists>"
     },
     "execution_count": 200,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(result8[\"就诊次数\"].index,result8[\"就诊次数\"].values)\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": "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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "result9 = df.groupby(\"month\")[\"医疗费用\"].mean()\n",
    "plt.plot(result9.index,result9.values)\n",
    "df[\"year\"] = df[\"入院日期\"].dt.year"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "outputs": [],
   "source": [
    "df[\"入院日期\"] = df[\"入院日期\"].astype(\"object\")"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "# 19"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "outputs": [
    {
     "data": {
      "text/plain": "       医疗费用\n治疗方案       \n休息     4900\n定期运动   3500\n控制饮食   3300\n清淡饮食   1150\n避免过敏源   750",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>医疗费用</th>\n    </tr>\n    <tr>\n      <th>治疗方案</th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>休息</th>\n      <td>4900</td>\n    </tr>\n    <tr>\n      <th>定期运动</th>\n      <td>3500</td>\n    </tr>\n    <tr>\n      <th>控制饮食</th>\n      <td>3300</td>\n    </tr>\n    <tr>\n      <th>清淡饮食</th>\n      <td>1150</td>\n    </tr>\n    <tr>\n      <th>避免过敏源</th>\n      <td>750</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 211,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 20\n",
    "result10 = df.groupby(\"治疗方案\")[[\"医疗费用\"]].sum()\n",
    "result10"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "outputs": [
    {
     "data": {
      "text/plain": "<BarContainer object of 5 artists>"
     },
     "execution_count": 213,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "result10.drop_duplicates()\n",
    "plt.bar(result10[\"医疗费用\"].index,result10[\"医疗费用\"].values)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}